Hi Janardhan
1. Doesn't matter, we can move them around depending on where we want them 2. Both should hopefully work fine. I have used some G Colab before really liked it, but again i think its up to you. 3. sure once we have a notebook we could automate some of the things. 4. Yes we have a docker container with systemds but G Colab does not support running this [1]. Again the reason i brought it up was because the notebooks I've seen was 50%+ setup of systemds. [1] https://github.com/googlecolab/colabtools/issues/299 Best regards Sebastian ________________________________ From: Janardhan <[email protected]> Sent: Wednesday, July 22, 2020 4:38:10 AM To: [email protected] Subject: Re: [DISCUSS] open for Jupyter notebook contributions, and end-to-end solutions. Hi all, This mail would help us structure the notebook files, Few questions: 1. Which directory should we stage the notebooks, is it a. samples/ b. notebooks/ 2. About the notebooks, they contain the notebook examples to work with [1] a. Google Colaboratory, b. Databricks platform (mostly MLContext related examples) in separate folders. 3. Sebastian - can we schedule a github workflow[2] i.e., step 1: notebook.ipynb (committed to systemds) step 2: notebook.html (generated by github workflow) step 3: notebook.html (committed to a `deploy` branch in systemds-website)[3] step 4: we will commit this file to our svn repo for systemds.apache.org 4. Sebastian - you have mentioned something about docker in this context, a. Is it about providing a jupyter server via a port? [1] https://github.com/j143/notebooks [2] https://github.com/j143/notebooks/pull/10 [3] https://github.com/j143/systemds-website/pull/8 Thank you, Janardhan On Thu, Jul 2, 2020 at 10:10 AM Janardhan <[email protected]> wrote: > Hi all, > > Now the SystemDS project scope has broadened from just ML to complete Data > Science life cycle, > in order to showcase our functionality, we are finding use cases for each > of the steps such as cleaning [1], > processing [2], and deploying on the cloud with end-to-end solutions (on > AWS or Google Cloud). > > [Note: OneDesign sponsoring $300 worth cloud resource if you are > developing a solution based on > AWS cloud with SystemDS also support in building cloud architecture valid > till July 2020, > reach out to the author of this mail :) ] > > We would like to keep the project open for notebook contributions, the > notebooks for both ML > and data processing use cases. (Idea borrowed from Apache Beam & > TensorFlow tutorials). > > Bonus: These notebooks have Google Colab compatibility to work on without > any configuration. > > *Questions:* > 1. Who will take ownership? > All the contributors are supporting this feature, in their respective > components. > > 2. Do you have a concrete implementation? > Yes, In fact, we have tested it. > Sample notebooks (Useful for researchers/engineers, start prototyping in > just 3 minutes) > a. Algorithms dev: > https://colab.research.google.com/github/j143/notebooks/blob/master/systemds_dev.ipynb > b. Deep learning: > https://gist.github.com/j143/df1fdea505df2c662b326bd689bf5a0d > c. SystemML library: > https://github.com/apache/systemds/tree/branch-1.2.0/samples/jupyter-notebooks > > 3. Will you mentor and review the PR? > Yes, we will mentor[3] the contributors and review the PRs in notebooks, > on request. > > [1] https://github.com/apache/systemds/pull/981 > [2] > https://github.com/apache/systemds/commit/8cbc85a949b3699cde8ed3cf3e3abec6a27fbc60 > [3] https://community.apache.org/mentoringprogramme.html > > Thank you, > Janardhan >
